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SMU Software Intensive
Systems Research Overview
Prepared by: LiGuo Huang
Computer Science & Engineering Department
Lyle School of Engineering
Southern Methodist University
DoD SERC Annual Research Review
Oct. 15-16, 2009
Departments in
SMU School of Engineering
• Engineering Management, Information and Systems
(EMIS)
Systems Engineering Program (SEP)
• Computer Science and Engineering (CSE)
• Mechanical Engineering (ME)
• Electrical Engineering (EE)
• Environmental and Civil Engineering (ENCE)
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAMSMU_SEP_Highlights_10.05.09
•Non-Degree Studies in SE
•SE Certificate Series
•MS SE
•PhD SE• On-Campus
• Internet
• Off-Campus Exec. Format
•Core-5
•Electives-• Current: 16
• In-Development: 9
•Developed in Response to
Industry & Government Needs
•Developed by SEP DT
SEP ACADEMIC PROGRAM
•3
Courses
•Resident
•Adjunct– Lockheed Martin
– Bell Helicopter
– Raytheon
– L3 Com
– MITRE Corp
– Siemens
– Abbott Laboratories
– Freescale Semiconductor
Experienced in Defense
Systems Development
Faculty
Customer DrivenPrograms
•Admissions – 1000+
•Graduates MS SE – 555
Employed full-time by A&D Sector
– U.S. Citizen
– DoD Security Clearance
Students
Delivery
SEP
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAMSMU_SEP_Highlights_10.05.09
• Modeling and Analysis of Defense Systems Development
• Technology Linkage, Selection and Transition to US Warfighter
• Systems Requirements Engineering and Integrated Verification &Validation
• Defense Systems Design and Development
SEP RESEARCH PROGRAM
•4
Funded Research– US Navy SPAWAR– DoD DAU– Lockheed Martin
• Complex System Design “Management Flight Simulator” Development
• Methodology for Optimizing Verification, Test and Evaluation Complex System Development
• Methodology for Measuring SoSDevelopment Performance
• Methodology for Analysis of Technology Alternatives
• 30 Students– 2 Full-Time– 28 Part-Time
• Lockheed Martin• U.S. Navy SPAWAR• Boeing• Raytheon
• 20 Applicants in Queue
Defense Systems
Research Projects
PhD SE and ASPhD SE Students
Research Areas
Defense Systems
Students
Research Focus
SEP
Selected
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAMSMU_SEP_Highlights_10.05.09
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Idea
SEP Concept
Development
SEP
Proposal
SMU
Proposal
SMU
TTU
UTA
UTD
Admit Students & Approve Degree
Plans
Deliver SE Courses
Develop SE Courses
Identify & Select Adjunct Faculty
Promote SEP
SEP Development Teamad hoc Systems
Engineering Council
SMU School of Engineering
Direct and Administer SEP
Deliver SE Courses
Advise PhD students
Industry and Government Volunteers
Promote SEP
Develop SE Courses
Develop Proposals
Identify & Select Adjunct Faculty
Identify & Capture Needs
SMU SEP ORIGIN AND DEVELOPMENT
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAMSMU_SEP_Highlights_10.05.09
SEP DEVELOPMENT
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAM
Name Organization Location
Arunski, Karl, P.E.** Texas Instruments, Inc. Dallas, TX
Coyne, Bill American Airlines Fort Worth, TX
Davis, Joe, P.E. Loral Vought Systems Grand Prairie, TX
Dean, Joe, Ph.D. Lockheed Martin Tactical Aircraft Systems Fort Worth, TX
Halligan, Charles General Electric Transportation Systems Erie, PA
Hanson, Harold EDS Plano, TX
Harris, Doug, DE Southern Methodist University Dallas, TX
Jain, Anant, Ph.D. Rockwell International Richardson, TX
Kolson, Joanna Federal Reserve Bank Dallas, TX
Luhks, Ronald, Ph.D. Loral Aerospace Houston, TX
Martin, Kim Abbott Labs Irving, TX
Pearse, Derek Hughes Training, Inc. Arlington, TX
Ransom, C. J. , Ph.D. Bell Helicopter Textron Arlington, TX
Stracener, Jerrell, Ph.D.* Vought/Northrop Grumman Corp. Grand Prairie, TX
Shaw, Terry, Ph.D. E-Systems Greenville, TX
Steinheimer, Steven L. E-Systems Garland, TX
Tucker, Scott Hughes Training, Inc. Arlington, TX
Vacante, Russell, Ph.D. Army Management Staff College Fort Belvoir, VA
Zsak, Mike U.S. DoD OSD Washington, DC
1991-1995
*=Chairman
**=Vice Chairman
Current DT
• PhD SE Start Up• MS SE Rev4• New SE Courses• Defense Systems Developer Needs-Driven
Curriculum Review w/INCOSE North Texas Chapter• Systems Design and Integration Track
Customer-Driven
SEP Development Projects
SEP Development Team MembershipDevelopment Model
Industry-Government-Student
Partnership
SEP Development Process
Organization Location
Abbott Laboratories Irving, TX
Abbott Laboratories Chicago, IL
Aerospace Quality Research and Development Dallas, TX
Agilecast Irving, TX
BAE Systems - Electronic Warfare Merrimack, NH
Bell Helicopter Hurst, TX
Boeing Aerospace Support Division Ft. Walton, FL
California Edison Rosemead, CA
CBI Dallas, TX
Diversified Technology, Inc Ridgeland, MS
Eaton Aerospace Fort,Worth, TX
Eaton Aerospace Jackson, MI
Elbit Systems Ft Worth, TX
Freescale Semiconductor Ausin, TX
Hewlett Packard Plano, TX
iWave Software, LLC Frisco, TX
JaCo Systems Dallas, TX
L-3 Communications Integrated Systems Greenville, TX
L-3, Communications Link Arlington, TX
Lockheed Martin Aeronautics Company Ft Worth, TX
Lockheed Martin Missiles & Fire Control Grand Prairie, TX
MAGNACOM, Inc. Huntsville, TX
Mitre Corp. Mclean, VA
NASA Johnson Space Center Houston, TX
NASA Marshall Huntsville, AL
Raytheon Space & Airborne System Plano, TX
Raytheon - Network Centric Systems McKinney, TX
Raytheon Integrated Defense Systems Andover, MA
Raytheon Intelligence & Information Systems Garland, TX
Raytheon Space and Airborne Systems Dallas,TX
Sandia National Labs Albuquerque, NM
Siemens Automation Richardson, TX
Siemens Government Services Richardson, TX
Spirit Aero Whichita, KS
Statistical Design Institute McKinney, TX
Strategic Thought Group Fort Worth, TX
Systems Design, LLC Acton, Ma
Texas Instruments Dallas, TX
Translog International Bristow, VA
U.S. Army Info Systems Engineering Com Ft. Huachuca, VA
U.S. Navy Naval Air Systems Command China Lake, CA
U.S. Navy SPAWAR Systems Center Charleston, SC
U.S. Navy SPAWAR System Center San Diego, CA
US Navy JTRS San Diego, CA
Vought Aircraft Industries Irving, TX
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAMSMU_SEP_Highlights_10.05.09
FRAMEWORK FOR RESPONSE TO DEFENSE CONTRACTORS AND DOD OPERATIONS PROBLEMS
•7
Concept
A&D Systems Developers DoD Operations
Problems Problems
Projects
Solutions
K-12Students
Faculty
Caruth Institute for Engineering Education
Lockheed Martin Skunk Works Lab® Systems Engineering
ProgramIndustry & Government
Team
Undergraduate Students
Graduate Students
Subject Matter Experts
Systems Engineering
Program
Lyle School of Engineering
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAMSMU_SEP_Highlights_10.05.09
SEP SUMMARY
•8
The SMU Systems Engineering Program was conceived (1991) and has been developed and administered in response to Dallas/Ft Worth region aerospace and defense systems developers, with focus on:
•U.S. AT&L/defense contractor workforce improvement by offering SE courses developed, delivered by defense industry subject matter experts
•Research conducted by SMU faculty, PhD students and SEP DT volunteers in response to defense systems developers priority needs in selected areas
Utilize SMU faculty* (resident and adjunct), DT members* and PhD SE students* with extensive experience (multiple company) on diverse U.S. defense development programs
Advanced Classified Programs – Sensor Programs – Missile Programs
* Most hold active DoD security clearance
Aircraft Programs
•F-35
•F-22 + ATF
•F/A-18
• F-16
• F-8
• A/FX
• A-12 +ATA
• A-10
• A-7
• B-2
• B-1
• B-52
• C-17
• C-130
• S-3
• V-22
SMU BOBBY B. LYLESCHOOL OF ENGINEERING
EMIS - SYSTEMS ENGINEERING PROGRAM
PROPOSED SERC RESEARCH PROJECTDEFENSE SYSTEMS REQUIREMENTS ENGINEERING AND V&V
•9
Phase 1 – Develop Top-Tier Guide for Engineering Requirements for Defense Systems and Integrated Validation & Verification of Requirements
BackgroundDefense Systems development program success begin with “right” requirements –LC-balanced, compatible, consistent, prioritized – depends on development cycle integrated V&V
Objectives• Purpose/Objectives
– To provide a unified guide for defense systems developers
– Reduce costs by integrated Modeling, Analysis and Simulation to more effectively utilize data and reduce testing
– Improve AT&L Workforce through capture of experience and practice from retiring component of workforce
• Benefits– To reduce testing for systems requirements
V&V– To reduce costs
Approach• Utilize D/FW region defense contractor
working groups using the SMU SEP DT to document current practice and capture prioritized needs
• Conduct literature and DoD/Industry survey of relevant guidance and methodologies
Sponsors and Collaborators• Sponsors
– Dallas/Ft Worth region defense contractors
• Funding– $ TBD for 2 years – Phase 1
• Collaborators– SMU : Jerrell Stracener– Texas A&M University : Abhijit Deshmukh– Texas Tech University : David A. Wyrick
Note: Currently an unfunded SMU SEP Research ProjectSEP_Research_10.05.09
Departments in
SMU School of Engineering
• Engineering Management, Information and Systems
(EMIS)
Systems Engineering Program
• Computer Science and Engineering (CSE)
• Mechanical Engineering (ME)
• Electrical Engineering (EE)
• Environmental and Civil Engineering (ENCE)
Research in Software Intensive SystemsDr. Jeff Tian, Dr. LiGuo Huang, Dr. Delores Etter
Software Verification & Validation, Risk Management and Dependability Improvement
Risk identification and management through systematic defect classification and analysis
Usage-based statistical testing to focus on high-usage/high-leverage operations and components
Integrated data analysis and reliability modeling
Evolvable risk reduction experience bases
Applications: Commercial, telecommunications, aerospace, web-based, e/web-service, and embedded systems
Focus: Systematic, risk-based dependability improvement
Complete Life-cycle Cost/Schedule/Quality Engineering
Integrated process and product measurements
Predictive cost/schedule/quality modeling and economic analysis
Value-based software quality engineering through stakeholder collaboration
Stakeholder-oriented hybrid process modeling & simulation
Automatic requirement traceability modeling for ease of developing, measuring and testing system-level non-functional requirement attributes.
Quality Aspects/Attributes: availability, reliability, safety, security, performance, usability, scalability, maintainability, etc.
Focus: stakeholder Win-Win cost/schedule/quality engineering throughout the entire life-cycle
Research in Software Intensive SystemsDr. Jeff Tian, Dr. LiGuo Huang, Dr. Delores Etter
Research in Security EngineeringDr. Suku Nair, Dr. Jeff Tian, Dr. LiGuo Huang
Coverage End-to-end security
Devices, networks, and systems security
Physical security (Access control)
Policies and logistics
Financial implications
Focus
Systems vs. Ad hoc Perspective
Process vs. Product Perspective
Business vs. Deployment Perspective
NSA Center of Excellence
CSE and SMU have been designated as a
National Center of Academic Excellence in
Information Assurance Education by NSA
and the Department of Homeland Security.
March 2006
HIGH ASSURANCE COMPUTING AND
NETWORKING LAB
Create an Authoritative Forum for the convergence of the needs
and solutions of Government, Industry, and Researchers
dedicated to addressing security issues
Partnership – first time that Lockheed Martin Skunk
Works® has partnered with an engineering program
Goal – Integrate the Skunk Works design philosophy into
the engineering program to make our students more
creative/innovative
Characteristics of Skunk Works projects include:
-rapid design/development,
-maximum use of commercial systems,
-small focused team
SMU/Skunk Works PartnershipDr. Delores Etter
SMU Participation in
Net-centric Software Engineering Consortium
and NSF I/UCRC
Net-centric Software Engineering Consortium Working with industrial/university partners since 2005
Focusing on system reliability, security, and safety of Net-centric software and systems
Emphasizing risk identification and management in system development life cycle
NSF I/UCRC of Net-Centric Software and Systems
Established in March 2009 (SMU/UTD/UNT)
an academia-industry collaborative approach of research and development in net-centric systems
Industrial members: Lockheed-Martin Aero, Raytheon, Boeing, Cisco, EDS/HP, Texas Instruments, T-Systems, Fujitsu, Codekko, GlobeRanger, Hall Financial Group
Software Data Quality and Estimation Research
In Support of Future Defense Cost Analysis (1)
Agency: DoD SERC
SMU Researcher: LiGuo Huang
Collaborator: USC Center for Systems and Software Engineering
Objective: Research and develop next generation of data definitions and estimation methods for complex software-intensive systems
Software Data Quality and Estimation Research
In Support of Future Defense Cost Analysis (2)
Coverage: Improve current cost estimation metrics, models and methods for software-
intensive systems (SISs) to reflect emerging changes in DOD SIS cost and process drivers.
Collect and analyze data to test hypothesis about SIS cost estimation metrics, models and methods (i.e., software sizing, reuse and productivity).
Explore alternative SIS cost estimation methods via data mining of SIS size, effort, and process data.
Develop chapters on DoD SIS software sizing, reuse and productivity for a Software Cost Estimation Metrics Manual.
Support the establishment of policy, related guidance, and recommended implementation approaches for data collection and analysis across all DoD acquisition programs which leverage existing and emerging data standards.
Develop and evolve an integrated SIS data repository and related tools which enable program assessment, cost analysis, SIS development risk assessment, and progress measurement.
Software Data Quality and Estimation Research
In Support of Future Defense Cost Analysis (3)
SMU Focus: Perform data mining of DoD project and cost data repositories to
determine relationships between shortfalls in SIS architecture & risk resolution and SIS rework effort.
Develop DoD-oriented case-based or analogy-based cost estimation models.
Expand data mining of DoD project and cost data repositories to determine commonalities and variabilities within and across different categories of DoD software projects.
Perform data mining of the new attributes of DoD project and cost data to determine commonalities and variabilities within and across different categories of DoD software projects.
Automatic Inference of Risk Reduction Knowledge Base(1)
Objective: Research and develop an automatic approach to constructing risk reduction knowledge base for complex software intensive systems
Collaborators: NASA JPL V&V
Motivation Example: The mishap of Mars Climate Orbiter (MCO) launched in late December, 1998.
What happened?
The MCO entered the Martian atmosphere at approximately 57km, not at its estimated 110km.
Unit mismatch among interoperating software subsystems/components. Ground navigation software used English units, not the required Metric units.. All other calculations were in metric.The discrepancy sent the spacecraft closer to the planet than its calculated trajectory indicated. Increased atmospheric stress destroyed the spacecraft.
Root Cause/Underlying Issues:
Verification & Validation:Development and V&V did not rely on the Software Interface
Specification (SIS) to ensure the software was compatible.
The mishap investigation board found no evidence of complete, end-to-end testing for the trajectory tracking software..
Current NASA JPL V&V Problems:
A lot of risk reduction experience from historical missions
Unstructured information scattered in historical documents
Automatic Inference of Risk Reduction Knowledge Base(2)
Risk
Repository
Constructor
Risk
Repository
Pattern Similarity
Analyzer and
Cluster
Reduced Risk
Respository
Closed Frequent
Itemset MinerRisk Terms
Files
Risk
Association
Rules Learner
Risk Association
RulesRisk analysis documents in
historical projects
Closed Frequent
Itemsets
Approach Overview:
Automatic Inference of Risk Reduction Knowledge Base(3)
Unstructured historical mission/project
risk reduction experience !
Organized historical mission/project
risk reduction rules !
Requirements Traceability for Large Scale Software
Intensive Systems (1)
Objective: Build a Hybrid Requirement Traceability (HRT) model to automatically trace system-level non-functional requirements to software functional requirements, design and code in order to quickly adapt to changes.
Approach: Apply text mining and Natural Language Processing techniques to
classify and cluster FRs and NFRs from process artifacts (e.g., requirements documents)
Verify with original requirements – identify erroneous requirement classification
Trace the requirement changes to system architecture design and to code through the HRT model
Reverse engineer the HRT model from the code to verify and validate the requirements.
Collaborator: NASA JPL
Requirement Traceability (3)
– Example Requirement Interdependency Graph for
Critical Resource Management System
Automate this !
Backup Charts
•26
• Task1: Verify FR/NFR clusters in real world large scale software applications
• Task 2: Explore automatic requirement conflict detection in large scale software applications
• Task 3: Explore the effectiveness of automatic requirement traceability recovery from code
o Explicit associations between NFR s and FRs.
o Semi-automatic NFR traceability through text mining and NPL techniques.
•Semi-automatic Hybrid Requirement Traceability (HRT) Model integrates FR/NFR tracing
• MAIN ACHIEVEMENT:
• Demonstrated semi-automatic hybrid requirement traceability model
improves effectiveness of NFR and FR traceability
improves measurability and testability of NFRs
improves adaptability to changes
reduces intensive manual efforts in NFR tracing
• HOW IT WORKS:
Apply text mining and Natural Language Processing techniques to classify and cluster FRs and NFRs from process artifacts
Automatically build FR and NFR interdependency graphs
Trace the requirement changes to system architecture design and to code through the HRT model
Reverse engineer the HRT model from the code to verify and validate the requirements.
• ASSUMPTIONS AND LIMITATIONS:
• Formatted requirement specifications (no specific templates are required)
• Complete requirement specification documents
•But, automatically clustering FRs and NFRs in process artifacts can improve and semi-automate requirement traceability
•More effective and efficient NFR and FR management and traceability
•Make it easier to trace, measure and test system level NFRs
•Better adaptability to changes
•System-level NFRs are difficult to trace, measure or test
•Traditional manual requirement traceability approaches requires intensive human efforts.
•Current research traces FR or NFR in separate models.
•Hybrid Requirement Traceability Model can reveal the FR and NFR conflicts
System-level NFRs can be automatically linked to related FRs
•Improvements and automation of NFR traceability
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SRequirement Traceability (2) – Research Overview
Hybrid Modeling and Simulation for
Trustworthy Software Process Management:
A Stakeholder-Oriented Approach
Objective: Research and develop stakeholder-oriented approach to hybrid process modeling and simulation for large scale software intensive systems (in distributed development setting)
Collaborators: USC Center for Systems and Software Engineering
Irish Software Engineering Research Centre
Two Dimensions of Process Modeling &
Simulation Concerns
•28
• Stakeholder Classes
• Process Phases
Stakeholder-based Hybrid Process Simulations:
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